Dear R users,
I am trying to estimate a nested logit model that has a constant option in
a degenerate partition. The data set is a conjoint survey where
respondents were asked to answer multiple choice sets. The choice sets
consist of three alternatives (described by four varying attributes) and a
no-choice option, i.e., none of the three alternatives. In the nested
model one branch should represent the three varying choice options and the
other branch the no-choice option. However, the R code I am using results
in an error message because the no-choice option is not varying in the
four attributes that I included in the mlogit formula. Is there another
way of coding the no-choice option in this way?
This is the R code I am using:
library(mlogit)
IA<-read.csv2("test.csv")
# attributes are R, H, J, V, each having three levels.
# r1, r2, h1, h2, etc are effect codes of these attribute levels.
nests = list(opt1 = c("Alt1", "Alt2", "Alt3"), opt2 = "NoChoice"),
unscaled=TRUE )
Error in solve.default(crossprod(attr(x, "gradi")[, !fixed])) :
Lapack routine dgesv: system is exactly singular
Thank you for your help!
Best,
Felix
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Felix Eggers